In the cockpit of an aircraft, a number of avionics systems, sometimes referred to as black boxes or line replaceable units (LRUs), are used to aid the flight crew in controlling the aircraft. Conventionally, only the flight management system (FMS) needed to have a navigation solution. The term "navigation solution" indicates that the system has a means of accurately determining the aircraft's position, direction of travel and velocity. Thus, accurately knowing this navigation information, the FMS can guide the aircraft for at least some period of time if other navigation aiding systems or devices became temporarily inoperative or unreliable. Today however, many systems in an aircraft are required to have navigation solutions. Examples of systems within an aircraft which frequently require navigation solutions include heads up displays (HUDs), transponders (TDRs) for broadcasting position information, flight data recorders (FDRs), entertainment systems, and enhanced ground proximity warning systems (EGPWSs) for providing terrain relief maps.
A problem facing avionics engineers is that all of these navigation solution dependent devices must be synchronized so that they all come to the same conclusion as to the navigation solution for the aircraft. If the various navigation solution dependent systems are not synchronized in this respect, different systems can come to different conclusions as to the navigation solution for the aircraft. Another constraint encountered when attempting to add multi-sensor navigation solution functionality to existing systems is the computational capacity of the individual systems. This renders it difficult or impossible for the systems to function together in providing the flight crew reliable information regarding the aircraft.
Today, almost all navigation solution dependent systems have GPS ARINC-743A inputs for receiving GPS information from a GPS receiver. These navigation solution dependent systems also frequently have other inputs from other systems to aid in the generation of their navigation solutions. For example, other inputs can come from an inertial reference system (IRS), distance measuring equipment (DME), a variable omnirange receiver (VOR), and an air data computer (ADC) system. One problem with navigation solution dependent systems which determine a navigation solution based upon inputs from multiple other systems is that there is typically not enough capacity on the databuses which connect the various systems to handle all of the parameter data (often referred to as "labels"). Parameter data includes data such as altitude data, air speed data, latitude data and longitude data. Further, in order to facilitate the generation of navigation solutions in this manner, the electrical and software connections between the various systems becomes very complex. This renders it difficult to upgrade individual systems when desired.
While it would be desirable to determine a navigation solution based primarily upon data from a GPS receiver, it is difficult for GPS receiver data to alone satisfy the various navigation solution requirements. Generally, navigation solutions must satisfy the following four requirements: (1) accuracy; (2) integrity; (3) availability; and (4) continuity. These criteria vary based upon the aircraft situation and other factors. Examples of navigation solution standards can be found in the following documents:
(1) FAA Technical Standard Order TSO C-129, Airborne Supplemental Navigation Equipment using the Global Positioning System (GPS);
(2) FAA Technical Standard Order TSO C-115b, Airborne Area Navigation Equipment Using Multi-Sensor Inputs;
(3) FAA Advisory Circular AC 20-130, Multi-Sensor Navigation Systems for use in the U.S. National Airspace System (NAS) and Alaska;
(4) FAA Advisory Circular AC 90-45A, Approval of Area Navigation Systems for use in the U.S. National Airspace System;
(5) RTCA DO-208, Minimum Operational Performance Standards for Airborne Supplemental Navigation Equipment using Global Positioning System (GPS);
(6) RTCA DO-187, Minimum Operational Performance Standards for Airborne Supplemental Navigation Equipment Using Multi-Sensor Inputs;
(7) RTCA DO-217 Change 2, Minimum Avionics System Performance Standards DGNSS Instrument Approach System: Special Category 1 (SCAT-1);
(8) RTCA DO-229, Minimum Operational Performance Standards for Global Positioning System/Wide Area Augmentation System Airborne Equipment; and
(9) FAA Notice N 8110.60, GPS as a primary Means of Navigation for Oceanic/Remote Operations.
The accuracy requirement of a navigation solution indicates the precision with which the navigation solution can predict the position or location of the aircraft. The integrity requirement is an error checking capability requirement. Closely correlated to the integrity requirement are the availability and continuity requirements. Availability relates to the percentage of the time that the navigation solution will be available. The continuity requirement relates to the percentage of the time that the navigation solution will remain available throughout an operation (for example a landing approach) once the operation has begun.
While GPS based navigation solutions are very accurate, they suffer problems with the correlated issues of integrity, availability and continuity. Based upon RTCA DO/208, Minimum Operational Performance Standards for Airborne Supplemental Navigation Equipment Using Global Positioning System (GPS), July, 1991, GPS can be used as a supplemental navigation system, using the Receiver Autonomous Integrity Monitor (RAIM) algorithm for detection of failures. However, to be used for sole means of navigation, a system must have sufficient redundancy such that if a component fails, it can both be detected and isolated or excluded so that navigation can continue with other components. The GPS satellite constellation lacks the redundancy needed for RAIM to isolate or exclude failed satellites with sufficient availability for sole means.
The Litton Autonomous Integrity Monitored Extrapolation (AIME) algorithm described in the previously listed references, which are herein incorporated by reference, combines GPS data from a GPS receiver with IRS data to satisfy the four requirements of a navigation solution. The AIME algorithm uses IRS data and adaptive Kalman filters to lessen the number of GPS satellites required. Kalman filters have infinite memories, with all past inputs affecting the present output. Using AIME, both the present position output and the detection and isolation of failures depend on the entire history of GPS measurements. The result is that less GPS satellites are required for the AIME algorithm to function. Thus, with less GPS satellites required, the navigation solution availability and continuity requirements are satisfied.
A method of implementing GPS/IRS navigation solution algorithms, such as the Litton AIME algorithm, is to provide a GPS input to the IRS where the algorithm is implemented. Then, the IRS can provide both a normal IRS output and a hybrid IRS output. The hybrid IRS output is an IRS output which is augmented with the GPS data to provide a navigation solution. Then, each system within the aircraft requiring an integrated navigation solution must receive and process the hybrid IRS output as a new input into their multi-sensor navigation solution. One problem with this method of implementation of a GPS/IRS navigation solution algorithm is that there frequently is insufficient databus or computational capacity for the hybrid IRS output parameter data to be received and/or processed by the various systems. An alternative to this method is to implement the GPS/IRS navigation solution algorithm in another apparatus, such as in the FMS, instead of in the IRS. However, both methods require extensive software changes to the FMS or other apparatus. Since the FMS typically includes several hundred thousand lines of code in its software, these methods are very difficult to implement. A second problem with this method of implementation is that the extensive modification and re-certification required to the number of systems affected can easily prove to be cost and schedule prohibitive. Consequently, a method of implementing a GPS/IRS navigation solution algorithm which overcomes these and other problems would be a significant advance in the art.